Metabolomic signatures associated with depression and predictors of antidepressant response in humans: A CAN-BIND-1 report

Giorgia Caspani, Gustavo Turecki, Raymond W. Lam, Roumen V. Milev, Benicio N. Frey, Glenda M. MacQueen, Daniel J. Müller, Susan Rotzinger, Sidney H. Kennedy, Jane A. Foster, Jonathan R. Swann

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

One of the biggest challenges in treating depression is the heterogeneous and qualitative nature of its clinical presentations. This highlights the need to find quantitative molecular markers to tailor existing treatment strategies to the individual’s biological system. In this study, high-resolution metabolic phenotyping of urine and plasma samples from the CAN-BIND study collected before treatment with two common pharmacological strategies, escitalopram and aripiprazole, was performed. Here we show that a panel of LDL and HDL subfractions were negatively correlated with depression in males. For treatment response, lower baseline concentrations of apolipoprotein A1 and HDL were predictive of escitalopram response in males, while higher baseline concentrations of apolipoprotein A2, HDL and VLDL subfractions were predictive of aripiprazole response in females. These findings support the potential of metabolomics in precision medicine and the possibility of identifying personalized interventions for depression.

Original languageEnglish (US)
Article number903
JournalCommunications Biology
Volume4
Issue number1
DOIs
StatePublished - Dec 2021
Externally publishedYes

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

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